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检索条件"任意字段=Proceedings of the 2019 3rd International Symposium on Computer Science and Intelligent Control"

共 342 条记录，以下是131-140 订阅

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Machine Learning Based Tongue Image Recognition for Diabetes Diagnosis 3rd

Machine Learning Based Tongue Image Recognition for Diabetes...

引用

3rd international Conference on Machine Learning for Cyber Security, ML4CS 2020

作者： Lin, Xiaohui Yu, Zhaochai Li, Zuoyong Liu, Weina Fujian Provincial Key Laboratory of Information Processing and Intelligent Control College of Computer and Control Engineering Minjiang University Fuzhou350121 China Department of Computer Engineering Fujian Polytechnic of Information Technology Fuzhou350003 China

ISBN: (纸本)9783030624620

Tongue diagnosis of Traditional Chinese Medicine (TCM) is of great significance in the diagnosis of diabetes. To reduce the subjectivity of doctors in clinical diagnosis, this paper proposes a method for diabetic tongue image recognition based on machine learning. Specifically, the proposed method first transforms an image from RGB (red, green and blue) color space to HSV (hue, saturation, and value) color space, and the hue component is transformed into an image with higher difference degree. Secondly, image thresholding and morphological operation are performed on the image to obtain the initial tongue body region. Thirdly, the proposed method performs image thresholding and morphological operations on the value component to achieve image binarization, and retains the largest connected region as the final tongue body region. Fourthly, iterative image thresholding is used to further segment the tongue body region into tongue coating and tongue nature. Finally, the proposed method extracts tongue color features, and uses SVM (support vector machine) and KNN (k-Nearest Neighbor) to achieve image recognition based diabetes diagnosis. Experimental results show that SVM achieves higher diabetic image recognition accuracy than KNN. © 2020, Springer Nature Switzerland AG.

关键词： Support vector machines

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A Platform for Coastline Monitoring System by Unmanned Surface Vessel 3

A Platform for Coastline Monitoring System by Unmanned Surfa...

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3rd international symposium on Autonomous Systems (ISAS)

作者： Geng, Chao Li, Guannan Xu, Hongli Northeastern Univ Sch Informat Sci & Engn Shenyang Peoples R China China Acad Sci CAS Shenyang Inst Automat State Key Lab Robot Shenyang Peoples R China China Acad Sci CAS Inst Robot & Intelligent Mfg Shenyang Peoples R China Univ Chinese Acad Sci Beijing Peoples R China

ISBN: (纸本)9781728112985

This paper presents a basic experiment platform to monitor coastline using unmanned surface vessel. This platform has two operating mode, manual work for release and automation for patrol. By swarm intelligent formation control and hunting strategy developed, we can use these methods for the monitor platform. The platform contains control system, sensor system, communication system. The USV (unmanned surface vessel) in the platform can patrol to ensure if there are dangerous situations in the area. They can switch mode to suit for different situation. In this paper, we design the platform system and manufacture the USV. We plan to use out USV to prove the platform.

关键词： Coastline Monitor Swarm intelligent USV Experiment Platform

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Event-triggered Formation control of Multi-agent Systems with Time Delay via Complex-valued Laplacian 3

Event-triggered Formation Control of Multi-agent Systems wit...

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3rd international symposium on Autonomous Systems (ISAS)

作者： Cao, Wenji Zhu, Wei Chongqing Univ Posts & Telecommun Key Lab Intelligent Anal & Decis Complex Syst Chongqing 400065 Peoples R China

ISBN: (纸本)9781728112985

Formation problem of first-order multi-agent systems is considered via complex-valued Laplacian. The event-triggered controller with time delay is designed for each agent. Formation can reach specific but arbitrary formation shape for some time delays under the assumption that the interconnection graph of the multi-agent systems is 2-rooted. Furthermore, the Zeno-behavior is excluded for the closed-loop system. Finally, a simulation example is given to illustrate the efficiency of the proposed results.

关键词： Event-triggered control Formation Multi-agent systems Complex-valued Laplacian Time delay

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Modelling and intelligent control of Micro PMBLDC for Surgical Robotic Applications 3

Modelling and Intelligent Control of Micro PMBLDC for Surgic...

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3rd international Conference on Computing and Network Communications, CoCoNet 2019

作者： Gandhi, Shreya U Prasad, B.K. Swathi Department of Electrical Engineering M.S. Ramaiah University of Applied Sciences Bangalore India

Micro motors in the robotic application have the advantage of lightweight, small size, more reliable and highly efficient. The objective of this study is to improve the speed characteristics of micro PMBLDC for surgical robot applications. In this paper, the micro PMBLDC for various configurations of inter pole is developed to obtain the desired torque and magnetic flux. The PID controller and fuzzy logic controller using ANFIS is proposed to regulate the speed response of the BLDC motor. The combination of PID and fuzzy logic in the closed-loop gives a steady-state error of 2.376%, and the use of a PID controller alone gives a steady-state error of 12.5%. With the proposed design of the controller for BLDC motor, the desired speed with lesser steady-state error obtained for surgical stapler application. © 2020 The Authors. Published by Elsevier B.V.

关键词： Simulink

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Overview of Task Understanding of Unmanned Combat Systems 3

Overview of Task Understanding of Unmanned Combat Systems

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3rd international symposium on Autonomous Systems (ISAS)

作者： Liu, Qingping Zhang, Jia Xin, Bin Zhang, Hao Bejing Inst Technol Sch Automat Beijing Peoples R China Bejing Inst Technol State Key Lab Intelligent Control & Decis Complex Sch Automat Beijing Peoples R China Bejing Inst Technol Beijing Adv Innovat Ctr Intelligent Robots & Syst Sch Automat Beijing Peoples R China

ISBN: (纸本)9781728112985

Unmanned combat systems, as new weapons to overturn the rules of future war, have been the focus of research and development of military powers. To realize the efficient combat coordination between human and unmanned systems, the task understanding of unmanned combat systems is critical. Concerning the task understanding problems of unmanned combat systems, the basic concepts and significance are first discussed Then the existing methods for the task understanding of unmanned systems are summarized and analyzed. A general process of the task understanding of unmanned combat systems and a task understanding framework based on deep learning are proposed The process defines the inputs, outputs, and triggering conditions. The deep learning based framework is capable of dealing with complex combat situations, which has certain reference significance for the task understanding of unmanned combat systems.

关键词： unmanned combat systems task understanding human-machine cooperation autonomy

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Analysis and design of intelligent environmental protection IOT system architecture based on GIS 3

Analysis and design of intelligent environmental protection ...

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2020 3rd international symposium on Big Data and Applied Statistics, ISBDAS 2020

作者： Min, Huang School of Information Engineering Guangzhou Nanyang Polytechnic Guangzhou Guangdong510925 China

With the third great change of the world's information industry, IOT will open an information age of interconnection of all things. The environmental protection Internet of things combines the traditional environmental protection industry with the Internet of things technology, realizes the practice of environmental protection informatization, is conducive to the construction of an all-round environmental protection governance system, speeds up the process of China's environmental protection informatization, and promotes the rapid transition from "digital environmental protection" to "intelligent environmental protection". With the continuous progress of cloud computing, big data and other cutting-edge technologies, environmental protection Internet of things has begun to integrate these technologies to better meet the needs of the public. In this paper, through the analysis and research of the application example of environmental protection Internet of things, summarizes the overall architecture of intelligent Internet of things system based on GIS for environmental protection. The overall architecture of the intelligent Internet of things system can be divided into four levels: field equipment, transmission network, IOT equipment management platform, environmental protection big data analysis and application platform. Using the IOT system architecture to design the IOT system platform can solve the repeated construction of infrastructure and software application system in the field of environmental protection, improve the traditional environmental governance mode and meet the public's right to know the environmental conditions. People can understand the real-time environmental information through mobile terminals or environmental protection cloud platform, and enterprises that cause pollution can use the network Anonymous reporting is carried out so that the public can participate in the national cause of ecological environment governance. © Published under licenc

关键词： computer architecture

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Peripheral Blood Leukocyte Image Segmentation Based on Deep Convolutional Neural Network 3rd

Peripheral Blood Leukocyte Image Segmentation Based on Deep ...

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3rd international Conference on Machine Learning for Cyber Security, ML4CS 2020

作者： Chen, Yuanyuan Teng, Shenghua Li, Zuoyong College of Electronics and Information Engineering Shandong University of Science and Technology Qingdao266590 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control College of Computer and Control Engineering Minjiang University Fuzhou350121 China

ISBN: (纸本)9783030624620

Counting and analysis of leukocyte on peripheral blood smears have great significance to assist doctors’ pathological diagnosis. Thus, accurate and automatic segmentation of leukocyte from blood smear images is a fundamental task. To achieve this task, we proposed an end-to-end peripheral blood leukocyte segmentation method based on deep convolutional neural networks, where the encoder-decoder network is its basic structure. Specifically, the proposed method first utilizes the feature encoder to extract multi-scale leukocyte features. Then, the context-aware feature decoder is introduced to reconstruct the segmentation mask of leukocyte. Finally, each layer generates a prediction map in the decoder module, and all these prediction maps are averaged to be the final prediction map. To demonstrate the effectiveness of the proposed method, we performed qualitative and quantitative comparisons with several existing methods on two publicly available datasets and a private dataset. Experimental results validate that the proposed method is superior for peripheral blood leukocyte image segmentation in terms of accuracy and robustness. © 2020, Springer Nature Switzerland AG.

关键词： Deep neural networks

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Data Mining in Hydroacoustic Systems: Statement of the Problem 3

Data Mining in Hydroacoustic Systems: Statement of the Probl...

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3rd international Conference on control in Technical Systems, CTS 2019

作者： Razmochaeva, Natalya V. Klionskiy, Dmitry M. Faculty of Computer Science and Technologies Saint-Petersburg Electrotechnical University 'Leti' Saint-Petersburg Russia

ISBN: (纸本)9781728125107

This paper presents the results of a study of approaches to the analysis of hydroacoustics data in the management of hydroacoustic systems. The basic classification is given (simple and complex hydroacoustic signals). The main stages and methods of signal processing are listed. The complexity of estimating the parameters of hydroacoustic signals and the problems of determining the parameters are noted. The weak elaboration of these issues and the relevance of the use of intelligent methods for their study are emphasized. The results of a study of the use of artificial neural networks in hydroacoustics are considered. The results show the viability of the discussed approach - the use of intelligent analysis in hydroacoustics. © 2019 IEEE.

关键词： Data mining

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Secrecy outage performance and deep learning evaluation of multihop energy harvesting IoT networks over Nakagami-m fading channels

Secrecy outage performance and deep learning evaluation of m...

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2020 international symposium on computer, Consumer and control, IS3C 2020

作者： Nguyen, Toan-Van Tran, Thong-Nhat Shim, Kyusung Huynh-The, Thien An, Beongku Dept. of Electronics and Computer Engineering in Graduate School Hongik University Korea Republic of ICT Convergence Research Center Kumoh National Institute of Technology Korea Republic of Dept. of Software and Communications Engineering Hongik University Korea Republic of

ISBN: (纸本)9781728193625

In this paper, we study the secrecy outage performance of multi-hop energy harvesting Internet-of-Things (IoT) networks, where all IoT devices harvest energy from a power beacon for conveying a confidential message to multiple legitimate users in the presence of an eavesdropper. To enhance the secrecy outage probability (SOP), we propose and analyze the best relay selection (BRE) and best-path selection (BPA) schemes under Nakagami-m fading environments. Based on the analysis results, we develop a deep learning model for the proposed schemes to evaluate the system SOP. Numerical results show that the BPA scheme greatly outperforms the BRE one, showing the efficiency of the best-path selection approach. Moreover, the deep learning model is capable of predicting the SOP of all schemes with high accuracy while it drastically reduces the execution time, arising a real-time configuration for multi-hop energy harvesting IoT networks. © 2020 IEEE

关键词： Energy harvesting

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Research on Automatic Target Detection and Recognition System Based on Deep Learning Algorithm 3rd

Research on Automatic Target Detection and Recognition Syste...

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3rd international Conference on Machine Learning for Cyber Security, ML4CS 2020

作者： Zhang, Qinghui Xu, Hongbin Li, Zhengyu Liu, Xiaobin Li, Yuxi Jiao, Yingjie Xi’an Modern Control Technology Research Institute Xi’an710065 China

ISBN: (纸本)9783030624620

Automatic target detection and recognition is the cornerstone of the intelligent unmanned systems to realize higher-level tasks. In this paper, the deep learning algorithm of Faster R-CNN was studied in depth, and the target detection model is designed combining the RPN network and the fast R-CNN. The target detection and recognition device with the ability of image acquisition and intelligent processing was also designed. Combining the device with the Faster R-CNN model, the automatic target detection and recognition system was developed. At last, the VGG-16 model was adopted for training the detection model, and the system was used for target detection experiments. The results show that the recognition accuracies of the system for the visible light images of trucks and tanks are 89.7% and 90.3%, respectively, and that for infrared images of tanks is 63.7%. Therefore, a good recognition effect has been achieved. This work provides a reference for the application of deep learning algorithms in the field of automatic target detection and recognition. © 2020, Springer Nature Switzerland AG.

关键词： Learning algorithms

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